Designing of an Immaculate Smart City with Cloud Based Predictive Analytics

Abstract

The major objective of a smart city is to provide ripest and rightest services to its residents with minimal human intervention. The data collected from various sensors, receptors and receivers can be stored in a reliable, cost effective and manageable cloud storage. Predictive analytics such as predictive modelling and machine learning can be used to analyze the latest and past data from the cloud to forecast the near and far future. The predictive analytics will immediately send notifications and the appropriate actions to be taken to the concerned system so that the residents can get equable life. Waste management such as sewage management and trash management are one of the major exertions in a smart city. In this paper, predictive analytics is applied on the cloud data collected from various sensors attached on the waste management resources such as trash bins and sewage pipes. Firstly, group of trash bins and sewage pipes are attached with radio wave sensors which in turn connected to an IoT enabled receiver to provide cost effective data collection. Secondly, the data from the receivers are stored in a cloud. Thirdly, predictive analytics using K-means clustering are proposed for applying on the data in the cloud. Finally, actions like redirecting the trash collection truck and sewage clearing robot based on the priority can be done automatically and long-term actions can be directed to the concerned authorities with notifications and alerts to take necessary actions. In this paper, designing of an immaculate smart city is proposed which can be achieved by developing IoT based trash collection and sewage cleaning system. For analysis purpose synthetic data is considered where levels for garbage cleaning bins at different time and liquid levels of drainage pipes at different time are represented with different numbers.